{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "56a6f16d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "\n",
    "\n",
    "url = \"https://api.bilibili.com/x/space/arc/search?mid=420221703&ps=30&tid=0&pn=1&keyword=&order=pubdate&jsonp=jsonp\"\n",
    "\n",
    "response = requests.get(url)\n",
    "\n",
    "responseJson = response.json()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "080e2045",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'comment': 6,\n",
       " 'typeid': 208,\n",
       " 'play': 392,\n",
       " 'pic': 'http://i2.hdslb.com/bfs/archive/bb2c3d912c6b2043a949cad7a796bfd4e4a4847a.jpg',\n",
       " 'subtitle': '',\n",
       " 'description': '多项式拟合；泰勒展开；Weierstrass第1/2逼近定理；Lagrange插值多项式',\n",
       " 'copyright': '1',\n",
       " 'title': '1.1. Example: Polynomial Curve Fitting - 3 - Nonlinear Response',\n",
       " 'review': 0,\n",
       " 'author': 'susongzhi',\n",
       " 'mid': 420221703,\n",
       " 'created': 1616334476,\n",
       " 'length': '36:23',\n",
       " 'video_review': 0,\n",
       " 'aid': 587236723,\n",
       " 'bvid': 'BV1fB4y1A7ew',\n",
       " 'hide_click': False,\n",
       " 'is_pay': 0,\n",
       " 'is_union_video': 0,\n",
       " 'is_steins_gate': 0,\n",
       " 'is_live_playback': 0}"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "responseJson[\"data\"][\"list\"][\"vlist\"][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "f4f3c517",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1-13-泛化能力及其上界](https://www.bilibili.com/video/BV1yt4y117LZ)  \n",
      "[1-14-正则化与过拟合](https://www.bilibili.com/video/BV1MQ4y1P7Qs)  \n",
      "[1-15-TPR-FPR曲线如何画](https://www.bilibili.com/video/BV1TQ4y1P7yZ)  \n",
      "[1-16-配方法求解最小二乘法](https://www.bilibili.com/video/BV1ev411z7C4)  \n",
      "[1-17-最小二乘法-凸函数优化的视角-计算图](https://www.bilibili.com/video/BV1FZ4y1W7Jh)  \n",
      "[1-18-核函数的视角看最小二乘法-类比思维](https://www.bilibili.com/video/BV1WK4y1t76s)  \n",
      "[1-19-什么是MLE？](https://www.bilibili.com/video/BV1Xt4y1C7RW)  \n",
      "[1-20-MLE与Fisher信息和Bregman散度](https://www.bilibili.com/video/BV1ZZ4y1n7k8)  \n",
      "[1-21-最小二乘法的MLE视角-E[w]/cov(w）](https://www.bilibili.com/video/BV1hZ4y1W7oy)  \n",
      "[1-22-MLE视角下的最小二乘法](https://www.bilibili.com/video/BV1UA411v7bx)  \n",
      "[1-23-什么是贝叶斯估计？](https://www.bilibili.com/video/BV1Rk4y1z7vp)  \n",
      "[1-24-单变量-高斯分布-均值-的贝叶斯估计](https://www.bilibili.com/video/BV1tv41167YU)  \n",
      "[1-25-线性回归模型的贝叶斯估计-part-1](https://www.bilibili.com/video/BV1gK411J7sZ)  \n",
      "[1-26-线性回归模型的贝叶斯估计-part2-预测分布](https://www.bilibili.com/video/BV15K411J7bH)  \n",
      "[1-27-线性回归模型的贝叶斯估计-举例说明](https://www.bilibili.com/video/BV1mT4y1j7Nf)  \n",
      "[1-28-线性回归模型的贝叶斯估计-总结](https://www.bilibili.com/video/BV1DK4y1e7EM)  \n",
      "[2-0-线性判别分类器-第二讲的主要内容是什么？](https://www.bilibili.com/video/BV1Q54y1m7wi)  \n",
      "[2-1-Logistic Regression - 模型的表示](https://www.bilibili.com/video/BV1Pp4y1v7dG)  \n",
      "[2-2-LR的决策面和损失函数](https://www.bilibili.com/video/BV1Jp4y1v7Xw)  \n",
      "[0-0-课程基本信息](https://www.bilibili.com/video/BV1QZ4y1A7VQ)  \n",
      "[0-1-0-人工智能的缘起-达特茅斯会议](https://www.bilibili.com/video/BV1WX4y1V7wM)  \n",
      "[0-1-1-机器学习-一种实现人工智能的途径](https://www.bilibili.com/video/BV1Jy4y177gc)  \n",
      "[0-1-2-两种观点：强人工智能 vs 弱人工智能](https://www.bilibili.com/video/BV1sy4y1a7gh)  \n",
      "[0-1-3-人工智能发展史上的三盘棋](https://www.bilibili.com/video/BV14f4y1477q)  \n",
      "[1.0 引言](https://www.bilibili.com/video/BV1Qb4y1X7xp)  \n",
      "[0-1-4-人工智能发展的四个阶段](https://www.bilibili.com/video/BV1qN411Q7TK)  \n",
      "[0-1-5-人工智能的五大流派](https://www.bilibili.com/video/BV1ih411Q7Hk)  \n",
      "[1.1. Example: Polynomial Curve Fitting - 1 - Line Fitting](https://www.bilibili.com/video/BV1Dv411h7rd)  \n",
      "[1.1 - Example: Polynomial Curve Fitting - 2 - Vector/Matrix Notation](https://www.bilibili.com/video/BV1sh411Q7wh)  \n",
      "[1.1. Example: Polynomial Curve Fitting - 3 - Nonlinear Response](https://www.bilibili.com/video/BV1fB4y1A7ew)  \n"
     ]
    }
   ],
   "source": [
    "for i in reversed(responseJson[\"data\"][\"list\"][\"vlist\"]):\n",
    "    print(\"[\"+i[\"title\"]+\"](https://www.bilibili.com/video/\"+i[\"bvid\"]+\")  \")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
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   "language": "python",
   "name": "python3"
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   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.6"
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 },
 "nbformat": 4,
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}
